A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is
Lecture Notes in Computational Science and Engineering
The Iterative Extraction approach (ITEX) extends the one-by-one extraction techniques in Principal Component Analysis to other additive data models. We describe additive models for clustering entity-to-feature and similarity data and apply ITEX for deriving computationally feasible clustering solutions. Specifically, two ITEX derived clustering methods, iK-Means and ADDI-S, are presented as well as update results on theoretical, experimental and applicational aspects of these methods.doi:10.1007/978-3-540-73750-6_6 fatcat:sqrj6qrt6nbq3oxt3go2baycpu